diff --git a/Kapitel 13/Tutorial.md b/Kapitel 13/Tutorial.md
index e81fa81..c171821 100644
--- a/Kapitel 13/Tutorial.md	
+++ b/Kapitel 13/Tutorial.md	
@@ -825,10 +825,22 @@ Das folgende Schaubild zeigt dir die konkrete Verkabelung
    ```
 
    ```bash
-      #!/bin/bash
+#!/bin/bash
 
 set -euo pipefail
 
+# Cleanup bei CTRL+C, SIGTERM, etc.
+cleanup() {
+    echo "[WARN] Analyse abgebrochen – prüfe auf ffmpeg-Leichen..."
+    pkill -P $$ ffmpeg || true
+    pkill -f "ffmpeg.*$VOD_ID" || true
+    # FIFO säubern (nur wenn gesetzt & vorhanden)
+    if [ -n "${FIFO_PATH-}" ] && [ -p "$FIFO_PATH" ]; then rm -f "$FIFO_PATH"; fi
+    exit 1
+}
+
+trap cleanup SIGINT SIGTERM
+
 # Umgebungsvariablen laden
 if [ -f "/etc/clipper/clipper.env" ]; then
     set -a
@@ -861,7 +873,7 @@ echo "[INFO] VOD gefunden: $VOD_PATH"
 echo "[INFO] Extrahiere WAV aus $VOD_PATH → $TMP_AUDIO"
 
 # Audio extrahieren mit Logging
-ffmpeg -v warning -i "$VOD_PATH" -ac 1 -ar 16000 -vn "$TMP_AUDIO" 2> "$TMP_LOG_AUDIO"
+nice -n 10 ffmpeg -v warning -threads 1 -i "$VOD_PATH" -ac 1 -ar 16000 -vn "$TMP_AUDIO" 2> "$TMP_LOG_AUDIO"
 echo "[OK] Audio extrahiert: $TMP_AUDIO ($(du -h "$TMP_AUDIO" | cut -f1))"
 
 echo "[INFO] Verwende Schwelle: $CLIPPER_PEAK_THRESHOLD"
@@ -931,6 +943,208 @@ with open(outfile, 'w') as f:
     json.dump(candidates, f)
 print(f"[DONE] {outfile} geschrieben mit {len(candidates)} Clip(s)")
 EOF
+
+echo "[INFO] Starte visuelle Analyse (alle 3 Sekunden ein Frame)..."
+
+TMP_FRAME_DIR="$TMP_DIR/frames"
+mkdir -p "$TMP_FRAME_DIR"
+
+# Videodauer ermitteln (in Sekunden)
+DURATION=$(ffprobe -v error -show_entries format=duration \
+  -of default=noprint_wrappers=1:nokey=1 "$VOD_PATH")
+DURATION=${DURATION%.*}
+
+INTERVAL=3
+EXPECTED_FRAMES=$(printf "%.0f" "$(echo "$DURATION / $INTERVAL" | bc -l)")
+
+echo "[INFO] VOD-Dauer: ${DURATION}s → erwarte ca. ${EXPECTED_FRAMES} Bilder bei fps=1/${INTERVAL}"
+
+# ffmpeg im Hintergrund
+START_TIME=$(date +%s)
+nice -n 10 ffmpeg -v warning -i "$VOD_PATH" \
+  -vf "fps=1/${INTERVAL},scale=160:90" \
+  "$TMP_FRAME_DIR/frame_%06d.bmp" &
+FFMPEG_PID=$!
+
+EXTRACTED_FRAMES=0
+LAST_LOGGED_FRAMES=0
+
+while kill -0 $FFMPEG_PID 2>/dev/null; do
+  EXTRACTED_FRAMES=$(find "$TMP_FRAME_DIR" -name 'frame_*.bmp' | wc -l)
+
+  if (( EXTRACTED_FRAMES > LAST_LOGGED_FRAMES )); then
+    NOW=$(date +%s)
+    ELAPSED=$((NOW - START_TIME))
+    ELAPSED_FMT=$(printf "%02d:%02d:%02d" $((ELAPSED/3600)) $((ELAPSED%3600/60)) $((ELAPSED%60)))
+
+    if (( EXTRACTED_FRAMES > 0 )); then
+      ESTIMATED_TOTAL=$((ELAPSED * EXPECTED_FRAMES / EXTRACTED_FRAMES))
+      ETA_SECONDS=$((ESTIMATED_TOTAL - ELAPSED))
+      ETA_FMT=$(printf "%02d:%02d:%02d" $((ETA_SECONDS/3600)) $((ETA_SECONDS%3600/60)) $((ETA_SECONDS%60)))
+    else
+      ETA_FMT="??:??:??"
+    fi
+
+    PERCENT=$(awk "BEGIN { printf \"%.2f\", $EXTRACTED_FRAMES * 100 / $EXPECTED_FRAMES }")
+    echo "[INFO] Lade Frame $EXTRACTED_FRAMES / $EXPECTED_FRAMES (${PERCENT}%) | ETA: $ETA_FMT | Elapsed: $ELAPSED_FMT"
+
+
+    LAST_LOGGED_FRAMES=$EXTRACTED_FRAMES
+  fi
+
+  sleep 1
+done
+
+# Final-Log
+EXTRACTED_FRAMES=$(find "$TMP_FRAME_DIR" -name 'frame_*.bmp' | wc -l)
+END_TIME=$(date +%s)
+TOTAL_TIME=$((END_TIME - START_TIME))
+TOTAL_FMT=$(printf "%02d:%02d:%02d" $((TOTAL_TIME/3600)) $((TOTAL_TIME%3600/60)) $((TOTAL_TIME%60)))
+
+echo "[INFO] Frame-Export abgeschlossen mit $EXTRACTED_FRAMES Bildern. Dauer: $TOTAL_FMT"
+
+echo "[INFO] Starte visuelle Analyse basierend auf Bewegung zwischen Frames..."
+
+TMP_JSON_VISUAL="$TMP_DIR/candidates.visual.json"
+
+/srv/clipper/.venv/bin/python3 <<EOF
+import os
+import json
+import cv2
+import numpy as np
+
+frame_dir = "$TMP_FRAME_DIR"
+output_json = "$TMP_JSON_VISUAL"
+
+frame_files = sorted([
+    os.path.join(frame_dir, f) for f in os.listdir(frame_dir)
+    if f.endswith(".bmp")
+])
+
+movement_threshold = 12000
+min_duration = 5
+candidates = []
+
+prev_frame = None
+active_start = None
+
+for idx, frame_path in enumerate(frame_files):
+    frame = cv2.imread(frame_path, cv2.IMREAD_GRAYSCALE)
+    if frame is None:
+        continue
+
+    if prev_frame is not None:
+        diff = cv2.absdiff(prev_frame, frame)
+        score = int(np.sum(diff))
+        print(f"[DEBUG] Frame {idx}: Bewegungsscore = {score}")
+
+        t = idx * 3
+
+        if score > movement_threshold:
+            if active_start is None:
+                active_start = t
+        else:
+            if active_start is not None and (t - active_start) >= min_duration:
+                # Pre/Post-Puffer hinzufügen
+                start_time = max(0, active_start - 2)
+                end_time = min(t + 2, len(frame_files) * 3)
+                candidates.append({
+                    "start": round(start_time, 2),
+                    "end": round(end_time, 2)
+                })
+                active_start = None
+
+    prev_frame = frame
+
+# Letzter offener Clip am Ende
+if active_start is not None:
+    t = len(frame_files) * 3
+    if t - active_start >= min_duration:
+        start_time = max(0, active_start - 2)
+        end_time = min(t + 2, len(frame_files) * 3)
+        candidates.append({
+            "start": round(start_time, 2),
+            "end": round(end_time, 2)
+        })
+
+with open(output_json, "w") as f:
+    json.dump(candidates, f)
+
+print(f"[DONE] Bewegungserkennung abgeschlossen → {len(candidates)} Clip(s) geschrieben in {output_json}")
+EOF
+
+
+echo "[INFO] Vergleiche Audio- und visuelle Kandidaten..."
+
+TMP_JSON_FINAL="$TMP_DIR/candidates.final.json"
+CLIPPER_MATCH_TOLERANCE="${CLIPPER_MATCH_TOLERANCE:-4.0}"
+
+/srv/clipper/.venv/bin/python3 <<EOF
+import json
+import os
+
+audio_file = "$TMP_JSON"
+visual_file = "$TMP_JSON_VISUAL"
+output_file = "$TMP_JSON_FINAL"
+tolerance = float("${CLIPPER_MATCH_TOLERANCE}")
+
+# Overlap mit Toleranz
+def overlap(a, b):
+    return not (a["end"] + tolerance < b["start"] or b["end"] + tolerance < a["start"])
+
+try:
+    with open(audio_file) as f:
+        audio = json.load(f)
+except:
+    print("[WARN] Audio-Kandidaten fehlen oder leer.")
+    audio = []
+
+try:
+    with open(visual_file) as f:
+        visual = json.load(f)
+except:
+    print("[WARN] Visuelle Kandidaten fehlen oder leer.")
+    visual = []
+
+combined = []
+only_audio = []
+only_video = visual.copy()
+matched_visual_indices = set()
+
+for a in audio:
+    matched = False
+    for idx, v in enumerate(visual):
+        if overlap(a, v):
+            combined.append({
+                "start": round(min(a["start"], v["start"]), 2),
+                "end": round(max(a["end"], v["end"]), 2)
+            })
+            matched_visual_indices.add(idx)
+            matched = True
+            break
+    if not matched:
+        only_audio.append(a)
+
+only_video = [
+    v for idx, v in enumerate(visual)
+    if idx not in matched_visual_indices
+]
+
+result = {
+    "only_audio": only_audio,
+    "only_video": only_video,
+    "combined": combined
+}
+
+with open(output_file, "w") as f:
+    json.dump(result, f)
+
+print(f"[DONE] Kandidaten klassifiziert → combined={len(combined)}, only_audio={len(only_audio)}, only_video={len(only_video)}")
+EOF
+
+echo "[INFO] Ersetze ursprüngliches JSON mit finaler Version..."
+mv "$TMP_JSON_FINAL" "$TMP_JSON"
+
    ```
    1. **SSH Node – Analyze VOD** (Node-Name: Analyze VOD)
       - Node-Typ: SSH